---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9973
- Wer: 0.3738
- Cer: 0.1499

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
| 4.7293        | 1.0   | 179  | 0.2498 | 1.0815          | 0.7089 |
| 1.5994        | 2.0   | 358  | 0.2279 | 0.7995          | 0.5767 |
| 0.9176        | 3.0   | 537  | 0.1536 | 0.6981          | 0.4359 |
| 0.4962        | 4.0   | 716  | 0.1715 | 0.6860          | 0.4339 |
| 0.2817        | 5.0   | 895  | 0.1346 | 0.7140          | 0.3806 |
| 0.2062        | 6.0   | 1074 | 0.1892 | 0.7249          | 0.4400 |
| 0.1654        | 7.0   | 1253 | 0.1203 | 0.7535          | 0.3534 |
| 0.1504        | 8.0   | 1432 | 0.1317 | 0.7843          | 0.3656 |
| 0.1499        | 9.0   | 1611 | 0.1677 | 0.7990          | 0.4059 |
| 0.1459        | 10.0  | 1790 | 0.1339 | 0.8195          | 0.3706 |
| 0.1409        | 11.0  | 1969 | 0.1334 | 0.8332          | 0.3632 |
| 0.1191        | 12.0  | 2148 | 0.1154 | 0.8286          | 0.3334 |
| 0.1046        | 13.0  | 2327 | 0.1385 | 0.8617          | 0.3722 |
| 0.0965        | 14.0  | 2506 | 0.1605 | 0.8756          | 0.4000 |
| 0.086         | 15.0  | 2685 | 0.1258 | 0.8674          | 0.3489 |
| 0.0747        | 16.0  | 2864 | 0.1688 | 0.8831          | 0.3948 |
| 0.0682        | 17.0  | 3043 | 0.1257 | 0.8814          | 0.3398 |
| 0.0635        | 18.0  | 3222 | 0.1366 | 0.9215          | 0.3569 |
| 0.0606        | 19.0  | 3401 | 0.1271 | 0.9136          | 0.3477 |
| 0.0477        | 20.0  | 3580 | 0.1273 | 0.9359          | 0.3456 |
| 0.0439        | 21.0  | 3759 | 0.1286 | 0.9150          | 0.3441 |
| 0.048         | 22.0  | 3938 | 0.1226 | 0.9309          | 0.3392 |
| 0.0429        | 23.0  | 4117 | 0.9718 | 0.3416          | 0.1249 |
| 0.0418        | 24.0  | 4296 | 0.9585 | 0.3389          | 0.1204 |
| 0.042         | 25.0  | 4475 | 0.9693 | 0.3636          | 0.1361 |
| 0.0353        | 26.0  | 4654 | 0.9719 | 0.3518          | 0.1309 |
| 0.0329        | 27.0  | 4833 | 0.9545 | 0.3617          | 0.1424 |
| 0.0288        | 28.0  | 5012 | 0.9910 | 0.3389          | 0.1257 |
| 0.0298        | 29.0  | 5191 | 0.9686 | 0.3380          | 0.1264 |
| 0.0242        | 30.0  | 5370 | 0.9915 | 0.3634          | 0.1488 |
| 0.0225        | 31.0  | 5549 | 0.9842 | 0.3349          | 0.1279 |
| 0.019         | 32.0  | 5728 | 0.9973 | 0.3738          | 0.1499 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1